John Feo

1.4k citations
66 papers · 895 · h-index 15

Impact in

Papers in

John Feo

59 papers receiving 818 citations

Peers

John Feo
Comparison fields: 5 of 62
  • Hardware and Architecture 491
  • Computer Networks and Communications 559
  • Computational Mathematics 9
  • Computer Vision and Pattern Recognition 194
  • Statistical and Nonlinear Physics 100
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Citations per field
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Citations per year

Countries citing papers authored by John Feo

Since Specialization
Citations

This map shows the geographic impact of John Feo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John Feo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Feo more than expected).

Fields of papers citing papers by John Feo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Feo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John Feo. The network helps show where John Feo may publish in the future.

Co-authors

The 25 scholars most cited alongside John Feo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John Feo Line = papers co-authored together John Feo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1990142
2 201070
3 200570
4 198858
5 201255
6 200550
7 200945
8 200730
9 201226
10 200226
11 199825
12
Comparative Study of Parallel Programming Languages: The Salishan Problems
199224
13 199023
14 201317
15 201515
16 201014
17
Performance and Programming Experience on the Tera MTA.
199913
18 200112
19
A report on the Sisal language project
199511
20 201411

About John Feo

John Feo is a scholar working on Computer Networks and Communications, Hardware and Architecture, Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics, having authored 66 papers that have together received 895 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (28 papers), Graph Theory and Algorithms (18 papers), Distributed and Parallel Computing Systems (18 papers), Advanced Database Systems and Queries (11 papers), Data Management and Algorithms (7 papers), Cloud Computing and Resource Management (7 papers), Distributed systems and fault tolerance (6 papers) and Advanced Data Storage Technologies (6 papers). The work is most often cited by research in Hardware and Architecture (491 citations), Computer Networks and Communications (559 citations), Computational Mathematics (9 citations), Computer Vision and Pattern Recognition (194 citations) and Statistical and Nonlinear Physics (100 citations). John Feo has collaborated with scholars based in United States, United Kingdom and Puerto Rico. Frequent co-authors include D.C. Cann, R. R. Oldehoeft, Daniel Chavarría-Miranda, Guojing Cong, David A. Bader, Yousu Chen, Zhenyu Huang, Shuangshuang Jin, Mahantesh Halappanavar and Alex Pothen. Their work appears in journals such as Parallel Computing, Journal of Parallel and Distributed Computing, Computer, Gastroenterology and ACM SIGPLAN Notices.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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